A network-based concept extraction for managing customer requests in a social media care context. (April 2020)

• Record Type: Journal Article
• Authors: Misuraca, Michelangelo; Scepi, Germana; Spano, Maria
• Is Part Of: International journal of information management. Volume 51(2020)
• Publication Date: 2020-04
• Subjects: Customer care -- Textual data -- Network analysis -- Community detection; Social sciences -- Information services -- Periodicals; Social sciences -- Research -- Periodicals; Information science -- Periodicals; Management information systems -- Periodicals; Knowledge management -- Periodicals; Sciences sociales -- Documentation, Services de -- Périodiques; Sciences sociales -- Recherche -- Périodiques; Sciences de l'information -- Périodiques; Systèmes d'information de gestion -- Périodiques; Information science; Management information systems; Social sciences -- Information services; Social sciences -- Research; Periodicals; Electronic journals; 025.52068
• DOI: 10.1016/j.ijinfomgt.2019.05.012
• Languages: English
• ISSNs: 0268-4012

Abstract

Highlights: Social media care is a new way for providing assistance to customers in a rapid way. Customer requests are usually short texts that it is not easy to automatically process. A strategy for extracting and managing knowledge from social media is presented. The proposal is tested on a set of tweets sent to the Apple Support on Twitter. Abstract: Web 2.0 changed everyday life in many aspects, including the whole system that orbits around the purchase of products and services. This revolution necessarily involved also companies, because customers became increasingly demanding. The diffusion of social media platforms pushed customers to prefer this channel for quickly obtaining information and feedback about what they want to buy, as well as for asking help after the selling. In this framework, many organisations adopted a new way of providing assistance known as social customer care. A direct link to companies allows customers to obtain real-time solutions. In this paper, we introduce a new strategy for automatically managing the information listed in the requests that customers send to the social media accounts of companies. Our proposal relies on the use of network techniques for extracting high-level structures from texts, highlighting the different concepts expressed into the customers' written requests. The texts can be then organised on the basis of this new emerging information. An application to the requests sent to the AppleSupport service on Twitter shows the effectiveness of the strategy.